Enhancing mobile mapping solutions with SBG Systems

GNSS post-processing, or PPK, is an approach where the raw GNSS data measurements logged on a GNSS receiver are processed after the data acquisition activity. They can be combined with other sources of GNSS measurements to provide the most complete and accurate kinematic trajectory for that GNSS receiver, even in the most challenging environments.

These other sources can be local GNSS base station at or near the data acquisition project, or existing continuously operating reference stations (CORS) typically offered by governmental agencies and/or commercial CORS network providers.

A Post-Processing Kinematic (PPK) software can make use of freely available GNSS satellite orbit and clock information, to help further improve the accuracy. PPK allow for precise determination of a local GNSS base station’s location in an absolute global coordinate reference frame datum, which is used.

PPK software can also support complex transformations between different coordinate reference frames in support of engineering projects.

In other words, it gives access to corrections, enhances the project’s accuracy, and can even repair data losses or errors during the survey or installation after the mission.

Bathymetry is the study and measurement of the depth and shape of underwater terrain, primarily focused on mapping the seafloor and other submerged landscapes. It is the underwater equivalent of topography, providing detailed insights into the underwater features of oceans, seas, lakes, and rivers. Bathymetry plays a crucial role in various applications, including navigation, marine construction, resource exploration, and environmental studies.

Modern bathymetric techniques rely on sonar systems, such as single-beam and multibeam echo sounders, which use sound waves to measure water depth. These devices send sound pulses toward the seafloor and record the time it takes for the echoes to return, calculating depth based on the speed of sound in water. Multibeam echo sounders, in particular, allow for wide swaths of the seafloor to be mapped at once, providing highly detailed and accurate seafloor representations.

Bathymetric data is essential for creating nautical charts, which help guide vessels safely by identifying potential underwater hazards like submerged rocks, wrecks, and sandbanks. It also plays a vital role in scientific research, helping researchers understand underwater geological features, ocean currents, and marine ecosystems.

Real-Time Kinematic (RTK) is a positioning technique where GNSS corrections are transmitted in near real time, typically using an RTCM format correction stream. However, there can be challenges in ensuring the GNSS corrections, specifically their completeness, availability, coverage, and compatibility.

The major advantage of PPK over RTK post processing is that the data processing activities can be optimized during post-processing, including forward and backward processing, whereas in real-time processing, any interruption or incompatibility in the corrections and their transmission will lead to lower accuracy positioning.

A first key advantage of GNSS post-processing (PPK) vs. real time (RTK) is that the system used on the field does not need to have a datalink/radio to feed the RTCM corrections coming from the CORS into the INS/GNSS system.

The main limitation to post processing adoption is the requirement of the final application to act on the environment. On the other hand, if your application can withstand the additional processing time needed to produce an optimized trajectory, it will greatly improve the data quality for all your deliverables.

A point cloud is a collection of data points in three-dimensional space that represents the external surface of objects or environments. Each point contains specific X, Y, and Z coordinates, and can include additional information such as color, intensity, or reflection values.

These datasets, which can contain millions or billions of points, are typically created by 3D scanners or other sensing devices. Point clouds are essential tools in various applications, including 3D modeling and visualization, Building Information Modeling (BIM), autonomous vehicle navigation, and quality inspection and control, making them a fundamental component of modern spatial data collection and analysis.

LiDAR technology and point cloud data are intrinsically connected as LiDAR sensors create point clouds by emitting laser pulses and measuring their return time. Each reflected laser pulse becomes a point in three-dimensional space, with specific X, Y, and Z coordinates.

These sensors can collect millions of points per second, generating highly detailed point cloud datasets that represent the scanned environment. The resulting point clouds are invaluable for various applications, including 3D mapping, terrain analysis, building surveys, and autonomous vehicle navigation systems, making LiDAR one of the primary technologies for generating accurate and detailed point cloud representations of the physical world.